The present invention generally relates to databases, and more particularly relates to characterizing workloads associated with databases.
Data warehouse and business intelligence workloads vary widely across customer implementations. The ad-hoc and scheduled work that enters the system is the root of the workload variation. Random numbers of users, data set size, and Structured Query Language (SQL) query complexity all contribute to the unpredictability. This results in effectively estimating and configuring the appropriate amount of hardware for the supporting database a difficult task. If the solution is undersized, the customer may suffer poor performance and possibly missed service level agreements (SLAs). In certain situations, this might force the provider to supply additional capacity for free. If oversized, the customer is left dissatisfied having spent more money than was necessary for the solution. In either case, when resource estimates are off target, customers are not happy.